Book Image

Mastering spaCy

By : Duygu Altınok
Book Image

Mastering spaCy

By: Duygu Altınok

Overview of this book

spaCy is an industrial-grade, efficient NLP Python library. It offers various pre-trained models and ready-to-use features. Mastering spaCy provides you with end-to-end coverage of spaCy's features and real-world applications. You'll begin by installing spaCy and downloading models, before progressing to spaCy's features and prototyping real-world NLP apps. Next, you'll get familiar with visualizing with spaCy's popular visualizer displaCy. The book also equips you with practical illustrations for pattern matching and helps you advance into the world of semantics with word vectors. Statistical information extraction methods are also explained in detail. Later, you'll cover an interactive business case study that shows you how to combine all spaCy features for creating a real-world NLP pipeline. You'll implement ML models such as sentiment analysis, intent recognition, and context resolution. The book further focuses on classification with popular frameworks such as TensorFlow's Keras API together with spaCy. You'll cover popular topics, including intent classification and sentiment analysis, and use them on popular datasets and interpret the classification results. By the end of this book, you'll be able to confidently use spaCy, including its linguistic features, word vectors, and classifiers, to create your own NLP apps.
Table of Contents (15 chapters)
1
Section 1: Getting Started with spaCy
4
Section 2: spaCy Features
9
Section 3: Machine Learning with spaCy

Transformers and TensorFlow

In this section, we'll dive into transformers code with TensorFlow. Pre-trained transformer models are provided to the developer community as open source by many organizations, including Google (https://github.com/google-research/bert), Facebook (https://github.com/pytorch/fairseq/blob/master/examples/language_model/README.md), and HuggingFace (https://github.com/huggingface/transformers). All the listed organizations offer pre-trained models and nice interfaces to integrate transformers into our Python code. The interfaces are compatible with either PyTorch or Tensorflow or both.

Throughout this chapter, we'll be using HuggingFace's pre-trained transformers and their TensorFlow interface to the transformer models. HuggingFace is an AI company with a focus on NLP and quite devoted to open source. In the next section, we'll take a closer look at what is available in HuggingFace Transformers.

HuggingFace Transformers

In the first...